DISSERTATION RESEARCH: Lizards of the Family Teiidae: phylogeny, historical biogeography, and continental-scale species delimitation

亚马逊赛跑者(Ameiva Ameiva)分布在四个截然不同的南美生态区，覆盖的面积比美国大陆还大。该项目将对这种蜥蜴物种进行第一次分布范围的系统地理研究，提供机会在该群体中发现隐蔽的多样性(即新物种)，并提供一个独特的机会来评估关于雨林和干燥生境多样化的相互竞争的假说。为亚马逊赛跑收集的数据也将用于解决气候变化对物种未来的风险。这项工作是与南美同事合作，研究关键的生理特征(例如，温度偏好和性能)，以重建物种分布模型并评估灭绝风险。因为对历史分布的建模是基于古气候数据，所以这些相同的模型可以用来预测气温上升对生物未来分布的影响。这项研究的结果将被开发成教学模块，用于向非生物专业的学生展示在假设检验中使用的真实世界观察，这里的重点是物种形成和生物地理学。来自研究人员广泛的实地和实验室工作的真实例子将为学生个性化数据，并提高他们对科学的多面性及其结论的性质的欣赏。初步结果表明，Ameiva Ameiva代表了一个物种复合体，这将通过对尽可能多的分布进行采样，并生成Sanger、NextGen和几类形态数据的组合来定义物种边界来进行测试。研究人员将参观巴西的三个爬行动物收藏品，以测量博物馆标本的形态数据。除了形态数据收集外，200个美洲斑潜蝇个体的100s-1000s SNPs(DdRADseq)将被纳入新开发的物种定界(SDL)方法。最近开发的一种集成了形态和分子数据的SDL贝叶斯方法(IBPP)被证明在各种情况下都表现良好，这将是本研究中使用的首选(但不是唯一的)方法。我们将使用SNP数据对南美洲亚马逊河和干对角线的多样化假设进行比较，这些程序允许对历史情景进行分析，并采用汇总方法估计每个假设的强度。

The Amazon racerunner (Ameiva ameiva) is distributed across four very different South American biomes that cover an area larger than the continental US. This project will perform the first distribution-wide, phylogeographic study of this lizard species, providing opportunities to find cryptic diversity in the group (i.e., new species) as well as a unique opportunity to evaluate competing hypotheses of diversification in both rainforests and dry habitats. Data collected for the Amazon racerunner will also be used to address future risk to species due to climate change. The work is a collaboration with South American colleagues to study key physiological traits (e.g., temperature preference and performance) to reconstruct species distribution models and assess extinction risk. Because modeling historical distributions is based on paleoclimate data, these same models can be used to predict the effect that increasing temperatures will have on future distributions of organisms. Results from this research will be developed into a teaching module and used to show non-Biology major students real-world observations used in hypothesis testing, here focused on speciation and biogeography. Real examples from the researchers' extensive field and lab work will personalize the data for students and enhance their appreciation of the multi-faceted nature of science, and the nature of its conclusions.Preliminary results suggests that Ameiva ameiva represents a complex of species, which will be tested by sampling as much of the distribution as possible, and generating a combination of Sanger, NextGen, and several classes of morphological data to define species boundaries. Researchers will visit three herpetological collections in Brazil to measure morphological data from museum specimens. In addition to morphological data collection, 100s-1000s of SNPs (ddRADseq) for 200 individuals of A. ameiva will be incorporated into newly developed species delimitation (SDL) methods. A recently developed SDL Bayesian approach that integrates morphological with molecular data (iBPP) was shown to perform well under a variety of scenarios, and this will be the preferred (but not exclusive) method used in this study. Diversification hypotheses for the Amazon and Dry Diagonal of South America will be compared using SNP data with programs that allow the analysis of historical scenarios and a summary approach to estimate the strength of each hypothesis.